Measurement Technologies for up- and Downstream Bioprocessing
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Biological Processes and Systems".
Deadline for manuscript submissions: closed (31 October 2020) | Viewed by 38800
Special Issue Editor
Special Issue Information
Dear Colleagues,
Real-time or just-in-time measurement technologies for bioprocesses are fundamental for advancing the basic understanding of bioprocesses, as well as for their control and optimization. Recent progress in smart sensors and spectroscopic methods together with more efficient management and evaluation of complex data has increased the possibilities of gaining relevant information in due time for critical decisions and to enable the control of bioprocesses. The ambitions of integrating steps and to continuously operate to reduce the (1) time for reaching production targets, (2) loss of yield, and (3) construction and maintenance costs of plants are the current trends in process development where new measurement techniques may play a key role.
This Special Issue on “Measurement Technologies for up- and Downstream Bioprocessing” is devoted to the recent developments in new measurement technologies toward these purposes. The currently unfolding developments—with new biological products for cell and gene therapy, and for treatments with monoclonal antibodies—also calls for new solutions regarding measurement technology. Examples of relevant topics may include:
- Novel optical methods with the capability of measuring minute impurity quantities;
- Imaging methods for timely measurement of the state of cells in a bioreactor culture;
- Measurement devices for at-line monitoring of critical quality attributes of the bioprocess;
- Machine learning strategies as a means to capture hidden information from real-time measurements;
- Measurement technologies for up- and downstream processes that favor the integration of a bioprocess.
Submissions on these and other topics related to the theme of this Special Issue are welcomed from researchers in both academia as well as industry.
Prof. Dr. Carl-Fredrik Mandenius
Guest Editor
Manuscript Submission Information
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Keywords
- real-time sensors
- bioprocesses
- online monitoring
- smart sensors
- machine learning
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